Statistical Optimization of Coal–Oil Agglomeration Using Response Surface Methodology

Abstract

ABSTRACTIn this study, a three-level and five-variable Box-Behnken design combined with response surface methodology (RSM) was used to develop an approach to analyze the behavior of different variables of oil agglomeration where pulp density, oil dosage, agglomeration time, particle size, and oil type were varied. The response of coal–oil agglomeration to this variation was investigated using the Box-Behnken design. The efficiency of this process was evaluated by calculating percent ash rejection (%AR) and percent organic-matter recovery (%OMR). The optimal conditions established were pulp density (3%), oil dosage (15%), agglomeration time (15 min), and particle size (0.15 µm) using linseed oil with a predicted %AR and %OMR as 66.02% and 95.93%, respectively, with a desirability of 94.20%. The optimal condition was experimentally validated as 64.60% for ash rejection and 93.94% for organic-matter recovery. The coefficient of determination (R2) was found to be .870 and .926 for %AR and %OMR, respectively.